CN116115260A

CN116115260A - High-resolution high-contrast fast-calculated transmission time sequence synchronous ultrasonic passive cavitation imaging method and system

Info

Publication number: CN116115260A
Application number: CN202310037068.6A
Authority: CN
Inventors: 路舒宽; 苏瑞波; 万春野; 万明习
Original assignee: Xian Jiaotong University
Current assignee: Xian Jiaotong University
Priority date: 2023-01-03
Filing date: 2023-01-10
Publication date: 2023-05-16
Anticipated expiration: 2043-01-10
Also published as: CN116115260B

Abstract

The invention discloses a high-resolution high-contrast rapid-calculation transmission time sequence synchronous ultrasonic passive cavitation imaging method and a system thereof: and the synchronous focusing ultrasonic transducer transmits and receives time sequences and acquires passive cavitation radio frequency signals, the vertex positioning coordinates of the focusing ultrasonic transducer are obtained according to a time delay superposition beam forming graph so as to accurately calculate absolute transit time, passive array simulation signals are constructed according to actual parameters and transducer space setting, a dimension conversion matrix is constructed by carrying out principal component analysis on self-adaptive weights obtained according to the passive array simulation signals, and rapid characteristic space self-adaptive beam forming is carried out on the passive cavitation radio frequency signals according to the dimension conversion matrix so as to obtain a synchronous ultrasonic passive cavitation imaging result of the transmitting time sequence. The invention is used for monitoring the hollow space-time dynamics evolution process in various ultrasonic cavitation applications through high resolution, high contrast and rapid reconstruction of cavitation images.

Description

High-resolution high-contrast fast-calculated transmission time sequence synchronous ultrasonic passive cavitation imaging method and system

Technical Field

The invention belongs to the technical field of ultrasonic detection and ultrasonic imaging, and relates to a high-resolution high-contrast rapid-calculation transmission time sequence synchronous ultrasonic passive cavitation imaging method and system.

Background

The cavitation effect generated by the ultrasonic wave acting on the medium is a physical basis of various therapeutic ultrasonic applications such as tissue ablation, tissue destruction, thrombolysis, blood brain barrier opening and the like, and the detection of cavitation is significant for clarifying cavitation physical mechanism and regulating and optimizing ultrasonic emission parameters. Ultrasonic imaging has the advantages of high imaging frame rate, deep imaging capability, low cost and the like, plays an important role in cavitation detection, and can be divided into active imaging based on a transmitting and receiving mode and passive imaging based on a non-transmitting and receiving-only mode (namely ultrasonic passive cavitation imaging). The ultrasonic passive cavitation imaging solves the problems of interference imaging of signals emitted by the focused ultrasonic transducer and interference cavitation activity of signals emitted by the ultrasonic imaging transducer in the traditional active imaging, can monitor the cavitation activity in real time in the process of focusing ultrasonic action, cannot interfere the cavitation activity, and has wide application prospect in various therapeutic ultrasonic applications.

Ultrasonic passive cavitation imaging initially employs a time-delay superposition integration method based on relative transit time information to reconstruct cavitation images, however, when imaging is performed using small-aperture ultrasonic transducers such as linear array transducers or phased array transducers, the method can generate excessive axial beams and be accompanied by serious interference artifacts, so that it is difficult to distinguish multiple cavitation sources in the axial direction. In order to solve the problem, researchers develop ultrasonic passive cavitation imaging methods based on robust beam forming, phase coherence coefficient weighting, frequency coupling beam forming, delay multiplication superposition beam forming and the like successively, and research results show that the methods inhibit interference artifacts and improve imaging resolution; however, due to the limitations of the diffraction modes of small aperture ultrasound imaging transducers, the axial resolution of the imaging results is still greatly limited.

The transmission time-sequence synchronous ultrasonic passive cavitation imaging technology is an imaging technology which strictly synchronizes the transmission time sequence of a focusing ultrasonic transducer with the receiving time sequence of an ultrasonic imaging transducer, and can process a received signal through absolute transit time information like ultrasonic active imaging, so that the axial resolution of an imaging result is not limited by a diffraction mode of a small-aperture ultrasonic transducer any more, but depends on the length of a transmission pulse of the focusing ultrasonic transducer, and the high axial resolution is obtained under the condition of short pulse transmission. The transmission time-sequence synchronous ultrasonic passive cavitation imaging technology is used for detecting cavitation nucleation in biological tissues, monitoring cavitation activity in blood brain barrier opening, characterizing sound field distribution of an ultrasonic transducer and the like, and is also combined with a pulse inversion technology to enhance detection sensitivity of weak cavitation signals in the blood brain barrier opening process. The beam synthesis processing is an important link for implementing a transmission time-sequence synchronous ultrasonic passive cavitation imaging technology, and a traditional delay superposition beam synthesis method is mainly adopted at present; however, this approach is non-adaptive, and it uses preset fixed weights independent of the received signal during beam forming, which can produce large main lobe sizes and high sidelobe levels, resulting in poor resolution and contrast of the imaging results, thereby compromising monitoring of cavitation activity.

The difficulty in transmitting time-synchronized ultrasound passive cavitation imaging is to simultaneously improve the resolution and contrast of the imaging results and achieve this with faster computational speeds, which is also an important requirement for a variety of ultrasound cavitation applications. In view of this, a high-resolution high-contrast fast-computing transmit-time-synchronization ultrasonic passive cavitation imaging technology is currently needed.

Disclosure of Invention

The invention aims to provide a high-resolution high-contrast rapid-calculation transmission time-sequence synchronous ultrasonic passive cavitation imaging method and system.

In order to achieve the above purpose, the present invention adopts the following technical scheme:

a high-resolution high-contrast fast-calculated transmission time-sequence synchronous ultrasonic passive cavitation imaging method comprises the following steps:

1) Synchronously triggering a pulse emitter/receiver and an ultrasonic imaging data acquisition system by utilizing a multichannel waveform generator to synchronize the time sequence of the emission of the focusing ultrasonic transducer and the receiving of the ultrasonic imaging transducer, acquiring cavitation sound radiation signals passively received by the ultrasonic imaging transducer by utilizing the ultrasonic imaging data acquisition system (namely acquiring cavitation sound radiation signals passively received by the ultrasonic imaging transducer under the condition of synchronizing the time sequence of the emission of the focusing ultrasonic transducer and the receiving of the ultrasonic imaging transducer), and obtaining and storing passive cavitation radio-frequency signals;

2) Setting pixel grids under an imaging coordinate system, calculating absolute transit time of each pixel point in the pixel grid corresponding to each vertex coordinate in a traversing set of vertex coordinates of a focused ultrasonic transducer, respectively carrying out delay superposition beam synthesis processing on a plurality of frames of passive cavitation radio frequency signals selected from the passive cavitation radio frequency signals acquired in the step 1 according to the absolute transit time to obtain delay superposition beam synthesis signals of each pixel point corresponding to each vertex coordinate in the traversing set, carrying out Hilbert transformation on the delay superposition beam synthesis signals of each pixel point corresponding to each vertex coordinate in the traversing set to obtain delay superposition beam synthesis images corresponding to each vertex coordinate in the traversing set, searching optimal vertex coordinates in the traversing set according to the delay superposition beam synthesis images corresponding to each vertex coordinate in the traversing set, and calculating the vertex positioning coordinates of the focused ultrasonic transducer according to the optimal vertex coordinates respectively found under the selected passive cavitation radio frequency signals of different frames;

3) Setting the scale of sound source radiation simulation signals and passive array simulation signals, setting the coordinates of each sound source in a simulation sound source group under an imaging coordinate system, calculating absolute transit time at each sound source in the simulation sound source group according to the vertex positioning coordinates of a focused ultrasonic transducer, constructing simulation signals of each array element of the ultrasonic imaging transducer according to the absolute transit time and the sound source radiation simulation signals, constructing array simulation signals of corresponding sound sources according to the simulation signals of each array element of the ultrasonic imaging transducer, and superposing the array simulation signals of each sound source to obtain the passive array simulation signals;

4) Calculating absolute transit time of each pixel point in the pixel grid according to the vertex positioning coordinates of the focused ultrasonic transducer, respectively extracting sampling points from the passive array simulation signals according to the absolute transit time to obtain full-aperture sampling signals of the corresponding pixel points, dividing the full-aperture sampling signals of the corresponding pixel points into a plurality of overlapped sub-aperture sampling signals, constructing sub-aperture sampling combined signals by utilizing the sub-aperture sampling signals, calculating covariance matrixes of the sub-aperture sampling combined signals, carrying out diagonal loading on the covariance matrixes, calculating self-adaptive weights of the corresponding pixel points according to the covariance matrixes after diagonal loading, carrying out principal component analysis on the self-adaptive weights of the pixel points to obtain principal component vectors, and constructing a dimension conversion matrix according to the principal component vectors;

5) Extracting and dividing the passive cavitation radio frequency signals of any frame acquired in the step 1 according to the absolute transit time calculated in the step 4 to obtain a plurality of overlapped sub-aperture sampling signals at corresponding pixel points, calculating a corresponding covariance matrix by utilizing sub-aperture sampling combined signals constructed by the sub-aperture sampling signals, carrying out diagonal loading on the covariance matrix, carrying out dimension reduction processing on the covariance matrix after diagonal loading by utilizing the dimension conversion matrix to obtain a low-dimensional domain covariance matrix at the corresponding pixel points, calculating a low-dimensional domain adaptive weight at the corresponding pixel points according to the low-dimensional domain covariance matrix, projecting the low-dimensional domain adaptive weight onto a signal subspace obtained by carrying out characteristic decomposition on the low-dimensional domain covariance matrix to obtain a low-dimensional domain characteristic space adaptive weight at the corresponding pixel points, calculating a low-dimensional domain sub-aperture sampling average signal at the corresponding pixel points according to the dimension conversion matrix and the sub-aperture sampling average signal, carrying out fast-phase-change on the low-dimensional domain characteristic space adaptive weight, carrying out fast-phase synthesis on the ultrasonic wave beam adaptive image, and carrying out fast-phase-inversion processing on the ultrasonic wave beam adaptive image, so as to obtain a fast-phase-change adaptive signal, and carrying out fast-phase-inversion processing on the ultrasonic image adaptive signal, thus obtaining the adaptive signal.

Preferably, in the step 1, the ultrasonic imaging transducer is one or more of diagnostic ultrasonic transducers such as a linear array transducer; the passive cavitation radio frequency signal is obtained by enabling the ultrasonic imaging transducer to work in a non-transmitting and receiving only mode (namely a passive receiving mode), synchronously focusing the time sequence of the ultrasonic transducer transmitting and the ultrasonic imaging transducer receiving through a multi-channel waveform generator, and acquiring the time sequence by an ultrasonic imaging data acquisition system.

Preferably, in the step 2, the length of the traversal interval of the x-axis coordinate, the y-axis coordinate and the z-axis coordinate of the vertex coordinate of the focusing ultrasonic transducer in the traversal set is not less than 10mm; the traversing step length of the x-axis coordinate and the y-axis coordinate is the pixel interval of the x-axis direction in the pixel grid, and the traversing step length of the z-axis coordinate is the pixel interval of the z-axis direction in the pixel grid.

Preferably, in the step 2, searching the optimal vertex coordinates in the traversal set specifically includes the following steps:

2.1 Counting the number of pixel points with pixel values larger than a pixel value threshold in the delay superimposed beam forming image corresponding to each vertex coordinate in the traversing set, wherein the pixel value threshold is 0.1-0.5 times of the maximum pixel value in the delay superimposed beam forming image;

2.2 Repeating the step 2.1 to obtain the pixel point number with the pixel value larger than the pixel value threshold value corresponding to each vertex coordinate in the traversing set, and searching the minimum pixel point number in the pixel point numbers, wherein the vertex coordinate corresponding to the minimum pixel point number is the optimal vertex coordinate.

Preferably, in the step 2, the vertex positioning coordinates of the focused ultrasound transducer are average values of optimal vertex coordinates corresponding to a plurality of frames (not less than 10) of passive cavitation radio frequency signals selected randomly.

Preferably, in the step 3, the sound source radiation simulation signal is a sine signal with a Hanning window, the time length of the sound source radiation simulation signal is consistent with the pulse length of the pulse signal emitted by the focused ultrasonic transducer, the frequency of the sound source radiation simulation signal is determined by the centroid frequency of the spectrum distribution of the passive cavitation radio frequency signal, and the sampling frequency of the sound source radiation simulation signal is consistent with the sampling frequency of the passive cavitation radio frequency signal; the scale of the passive array simulation signal is consistent with the scale of the passive cavitation radio frequency signal.

Preferably, in the step 3, the space setting of the transducer used for calculating the absolute transit time at each sound source in the simulated sound source group is the same as the space setting of the focused ultrasound transducer and the ultrasound imaging transducer in the step 1.

Preferably, in the step 3, the simulation signal of any array element of the ultrasonic imaging transducer in the constructed array simulation signal of any sound source is expressed as:

wherein, the liquid crystal display device comprises a liquid crystal display device,

i=1, 2, N for simulation signals of the i-th array element in the array simulation signals of the m-th sound source in the simulated sound source group _E ，N _E For the number of array elements of the ultrasound imaging transducer, k=1, 2,.. _S ，N _S For the number of samples of the passive cavitation radio frequency signal, m=1, 2,.. _A ，N _A For simulating the number of sound sources in a sound source group round {. } means round-round, round ++>

For absolute transit time at mth sound source calculated from focused ultrasound transducer vertex positioning coordinates, τ _Trig Triggering delay for collecting cavitation sound radiation signals by an ultrasonic imaging data collecting system, wherein fs is the sampling frequency of passive cavitation radio frequency signals, and s _ae For sound source radiation simulation signal->

The number of sampling points of the simulated signal is radiated for the sound source.

Preferably, in the step 4, the spatial arrangement of the transducer used for calculating the absolute transit time at each pixel point in the pixel grid is the same as the spatial arrangement of the focused ultrasound transducer and the ultrasound imaging transducer in the step 1.

Preferably, in the step 4, the covariance matrix after diagonal loading is expressed as:

and->

Respectively, the first, the first+1th and the third in the full aperture sampling signal at the jth pixel point obtained from the passive array simulation signalSignals of the first +L-1 array element,

and->

The method comprises the steps of respectively obtaining a sub-aperture sampling signal, a sub-aperture sampling combined signal, a covariance matrix of the sub-aperture sampling combined signal and a covariance matrix after diagonal loading at a j-th pixel point corresponding to a passive array simulation signal, wherein l=1, 2, & gt, N _E -l+1, L is the length of the sub-aperture, j=1, 2,.. _P ，N _P Is the number of pixels +.>

Coordinate of the jth pixel, [ · ]] ^T Representing the transpose, [] ^H The conjugate transpose is represented, delta is the diagonal loading factor, trace {.cndot } represents the trace calculation, and I is the identity matrix.

Preferably, in the step 4, the length L of the sub-aperture is N _E And/2, the diagonal loading factor delta is 1/L.

Preferably, in the step 4, the main component analysis of the adaptive weights at each pixel point specifically includes the following steps:

and taking the self-adaptive weight at each pixel point in the pixel grid calculated according to the passive array simulation signal as a sample, calculating a covariance matrix of the self-adaptive weight, and then carrying out feature decomposition on the covariance matrix to obtain L feature vectors corresponding to L feature values arranged in a descending order, namely obtaining L principal component vectors.

Preferably, in the step 4, the construction of the dimension conversion matrix specifically includes the following steps:

selecting the first Q principal component vectors v corresponding to the maximum eigenvalue from the L principal component vectors ₁ ,v ₂ ,...,v _Q-1 ,v _Q And vector v of principal components _Q The elements being replaced by elements

The resulting dimensional transformation matrix is expressed as:

C＝[v ₁ ,v ₂ ,...,v _Q-1 ,dc]。

preferably, in the step 2, the step 3 and the step 4, the calculating of the absolute transit time specifically includes the following steps:

s1, establishing a three-dimensional position coordinate system by taking the center of an ultrasonic imaging transducer as an origin, taking the transverse direction and the axial direction of the ultrasonic imaging transducer as an x-axis and a z-axis respectively, and taking the direction perpendicular to an imaging plane of the ultrasonic imaging transducer as a y-axis;

s2, deleting a y-axis from the three-dimensional position coordinate system to obtain an imaging coordinate system;

s3, establishing an equation of a tangent line or a tangent plane at the vertex of the focused ultrasonic transducer:

for the transducer space setting I, the equation of tangent line at the vertex of the focused ultrasound transducer is:

sinα(x-x ^V )+cosα(z-z ^V )＝0

for the transducer space setting II, the equation of the tangential plane at the vertex of the focused ultrasound transducer is:

sinα(y-y ^V )+cosα(z-z ^V )＝0

wherein x is ^V And z ^V Respectively an x-axis coordinate and a z-axis coordinate of a vertex of the focused ultrasonic transducer in the three-dimensional position coordinate system, y ^V A y-axis coordinate of a vertex of the focused ultrasonic transducer in the three-dimensional position coordinate system; in the space setting I of the transducer, the central axis of the focusing ultrasonic transducer is in the imaging plane of the ultrasonic imaging transducer, and alpha is more than or equal to 0 and less than or equal to pi/2; in the space setting II of the transducer, the central axis of the focusing ultrasonic transducer is intersected with the imaging plane of the ultrasonic imaging transducer and is perpendicular to the transverse direction of the ultrasonic imaging transducer, and alpha is more than 0 and less than or equal to pi/2; alpha is an included angle between the central axis of the focused ultrasonic transducer and the central axis of the ultrasonic imaging transducer;

S4, establishing a calculation formula of the distance from a point in an imaging coordinate system to a tangent line or a tangent plane at the vertex of the focused ultrasonic transducer:

for the transducer space setting I, the calculation formula of the distance from the point with the coordinates of (x, z) to the tangent line at the vertex of the focused ultrasonic transducer is as follows:

d ¹ (x,z)＝|sinα(x-x ^V )+cosα(z-z ^V )|

wherein, |·| represents taking absolute values;

for the transducer space setting II, the calculation formula of the distance from the point with the coordinates of (x, z) to the tangent plane at the vertex of the focused ultrasonic transducer is as follows:

d ¹ (x,z)＝|-sinα(y ^V )+cosα(z-z ^V )|

s5, establishing a calculation formula of the distance from a point with coordinates (x, z) in an imaging coordinate system to each array element of the ultrasonic imaging transducer:

wherein i=1, 2,.. _E ，

Coordinates of an ith array element of the ultrasonic imaging transducer;

s6, establishing a calculation formula of absolute transit time according to the calculation formula of the distance in the steps S4 and S5:

τ _i (x,z)＝[d ¹ (x,z)+d _i ² (x,z)]/c

where c is the speed of sound propagation.

For the calculation formulas in steps S4 to S6:

let (x, z) be the coordinates of any pixel point in the pixel grid

Parallel instruction (x) ^V ,y ^V ,z ^V ) Obtaining absolute transit time at any pixel point corresponding to any vertex coordinate in the step 2 for any vertex coordinate in the traversing set of the vertex coordinates of the focusing ultrasonic transducer;

let (x, z) be the coordinates of any sound source in the simulated sound source group

Parallel instruction (x) ^V ,y ^V ,z ^V ) Locating coordinates (x) for focused ultrasound transducer vertices ^VL ,y ^VL ,z ^VL ) Obtaining the absolute transit time of any sound source in the step 3;

let (x, z) be the coordinates of any pixel point in the pixel grid

Parallel instruction (x) ^V ,y ^V ,z ^V ) Locating coordinates (x) for focused ultrasound transducer vertices ^VL ,y ^VL ,z ^VL ) The absolute transit time at any pixel point in step 4 is obtained.

Preferably, in the step 5, the formula of calculating the low-dimensional domain covariance matrix is:

/>

where j=1, 2,.. _P ，

And->

Respectively a low-dimensional domain sub-aperture sampling combined signal and a sub-aperture sampling combined signal at a j pixel point corresponding to a p-th frame passive cavitation radio frequency signal, wherein ζ is +.>

The ratio of the sum of the squares of the elements to the number of sub-aperture sampled signals.

Preferably, in the step 5, the dimension of the signal subspace obtained by the low-dimensional domain covariance matrix through feature decomposition is determined according to a cross spectrum measurement method, wherein the cross spectrum measurement coefficient is 1% -5%.

Preferably, in the step 5, the calculation formula of the low-dimensional domain sub-aperture sampling average signal is:

where j=1, 2,.. _P ，

And the first sub-aperture sampling signal at the j pixel point corresponding to the p-th frame passive cavitation radio frequency signal.

A high resolution high contrast fast calculated transmit time-synchronized ultrasonic passive cavitation imaging system, the system comprising a master control computer, a focused ultrasonic transducer, an ultrasonic imaging transducer and a multi-channel waveform generator for synchronizing the transmit time sequences of the focused ultrasonic transducer and the receive time sequences of the ultrasonic imaging transducer, wherein the master control computer comprises software (the master control computer is also used for storing the passive cavitation radio frequency signals) for processing the passive cavitation radio frequency signals obtained by collecting cavitation sound radiation signals passively received by the ultrasonic imaging transducer and generating transmit time-synchronized ultrasonic passive cavitation imaging results, and the software comprises a focused ultrasonic transducer vertex positioning coordinate calculation module, a passive array simulation signal construction module, a dimension conversion matrix construction module, a fast feature space self-adaptive beam forming module and an image display module;

The focused ultrasound transducer vertex positioning coordinate calculation module is used for executing the step 2), and is mainly used for setting pixel grids under an imaging coordinate system, calculating absolute transit time of each pixel point in the pixel grid corresponding to each vertex coordinate in a focused ultrasound transducer vertex coordinate traversal set, respectively carrying out delay superposition beam forming processing on a plurality of frames of passive cavitation radio frequency signals selected from the acquired passive cavitation radio frequency signals according to the absolute transit time, carrying out Hilbert transformation on delay superposition beam forming signals at each pixel point corresponding to each vertex coordinate in the traversal set obtained by processing, searching optimal vertex coordinates in the traversal set according to delay superposition beam forming diagrams corresponding to each vertex coordinate in the traversal set obtained by transformation, and calculating focused ultrasound transducer vertex positioning coordinates according to the optimal vertex coordinates respectively found under the selected passive cavitation radio frequency signals of different frames;

the passive array simulation signal construction module is used for executing the step 3), and is mainly used for setting the scale of sound source radiation simulation signals and passive array simulation signals, setting the coordinates of each sound source in a simulation sound source group under an imaging coordinate system, calculating absolute transit time at each sound source in the simulation sound source group according to the focus ultrasonic transducer vertex positioning coordinates obtained by the focus ultrasonic transducer vertex positioning coordinates calculation module, constructing simulation signals of each array element of an ultrasonic imaging transducer according to the absolute transit time and the sound source radiation simulation signals, constructing array simulation signals of corresponding sound sources according to the simulation signals of each array element of the ultrasonic imaging transducer, and obtaining the passive array simulation signals by superposing the array simulation signals of each sound source;

The dimension conversion matrix construction module is used for executing the step 4), and is mainly used for calculating absolute transit time at each pixel point in the pixel grid according to the focus ultrasonic transducer vertex positioning coordinates obtained by the focus ultrasonic transducer vertex positioning coordinates calculation module, respectively extracting sampling points from the passive array simulation signals obtained by the passive array simulation signal construction module according to the absolute transit time, dividing the full-aperture sampling signals at the corresponding pixel points obtained by extraction into a plurality of overlapped sub-aperture sampling signals and utilizing the sub-aperture sampling signals to construct a sub-aperture sampling combined signal, calculating a covariance matrix of the sub-aperture sampling combined signal, carrying out diagonal loading on the covariance matrix, calculating self-adaptive weights at the corresponding pixel points according to the covariance matrix after the diagonal loading, carrying out principal component analysis on the self-adaptive weights at each pixel point, and constructing a dimension conversion matrix according to principal component vectors obtained by analysis;

the fast feature space adaptive beam forming module is used for executing the step 5), and is mainly used for extracting and dividing a plurality of overlapped sub-aperture sampling signals at corresponding pixel points from any frame of acquired passive cavitation radio frequency signals according to the absolute transit time calculated in the dimension conversion matrix constructing module, calculating a corresponding covariance matrix by utilizing sub-aperture sampling combined signals constructed by the sub-aperture sampling signals and carrying out diagonal loading on the covariance matrix, carrying out dimension reduction processing on the covariance matrix after diagonal loading by utilizing the dimension conversion matrix obtained by the dimension conversion matrix constructing module, calculating low-dimension domain adaptive weights at the corresponding pixel points according to the low-dimension domain covariance matrix at the corresponding pixel points obtained by the dimension reduction processing, projecting the low-dimension domain adaptive weights onto signal subspaces obtained by the low-dimension domain covariance matrix through feature decomposition, calculating low-dimension domain sub-aperture sampling average signals at the corresponding pixel points according to the dimension conversion matrix and the sub-aperture sampling signals, and carrying out fast synthesis on the low-dimension domain adaptive signals at the corresponding pixel points according to the low-dimension domain adaptive weights at the corresponding pixel points obtained by projection, and carrying out fast synthesis on the fast synthesis of the feature space adaptive signal at the corresponding pixel points by the fast synthesis point space adaptive wave beam forming module;

The image display module is used for carrying out normalization and logarithmization processing on the rapid characteristic space self-adaptive beam forming diagram obtained by the rapid characteristic space self-adaptive beam forming module, displaying a transmission time sequence synchronous ultrasonic passive cavitation imaging result corresponding to any frame of passive cavitation radio frequency signals obtained by processing, or dynamically displaying a transmission time sequence synchronous ultrasonic passive cavitation imaging result corresponding to a plurality of frames of passive cavitation radio frequency signals.

The beneficial effects of the invention are as follows:

according to the high-resolution high-contrast rapid-calculation transmission time-sequence synchronous ultrasonic passive cavitation imaging method, after the transmission and receiving time sequences are synchronously transmitted and the passive cavitation radio frequency signals are acquired, the vertex positioning coordinates of the focused ultrasonic transducer are calculated, the passive array simulation signals are constructed, the dimension conversion matrix is constructed according to the vertex positioning coordinates, the rapid feature space self-adaptive beam synthesis is performed, the resolution and the contrast of the transmission time-sequence synchronous ultrasonic passive cavitation imaging are effectively improved, and meanwhile the imaging calculation speed is improved. The imaging method provided by the invention can accurately and dynamically monitor the space-time dynamics evolution process of various ultrasonic cavitation application hollow activities such as high-intensity tissue damage, low-intensity blood brain barrier opening and the like in real time, and lays a solid foundation for clarifying cavitation physical mechanisms and related biological mechanisms behind the application and regulating and optimizing ultrasonic emission parameters.

The invention uses the multi-channel waveform generator to transmit the trigger signal to synchronize the time sequence of focusing the ultrasonic transducer transmission and ultrasonic imaging transducer receiving, thereby utilizing absolute transit time to process the passive cavitation radio frequency signal, so that the axial resolution of ultrasonic passive cavitation imaging is not limited by the diffraction mode of the transducer, depends on the time length of the transmitted pulse, and can obtain high axial resolution under the short pulse transmission situation. According to the time delay superposition beam forming diagram corresponding to any vertex coordinate in the traversing set of the vertex coordinates of the focused ultrasonic transducer, the optimal vertex coordinates are searched from the traversing set, and the vertex positioning coordinates of the focused ultrasonic transducer are calculated, so that the focused ultrasonic transducer can be accurately positioned in a three-dimensional position coordinate system, and the calculation accuracy of absolute transit time is improved. According to the invention, the passive array simulation signals are constructed by a numerical simulation method, the dimension conversion matrix is constructed by utilizing the passive array simulation signals, and then any frame of passive cavitation radio frequency signals are processed by utilizing the dimension conversion matrix, so that the corresponding dimension conversion matrix is not required to be constructed each time when each frame of passive cavitation radio frequency signals are processed, and the dimension conversion matrix is not required to be constructed by a pre-experiment method; the dimensional transformation matrix obtained by the numerical simulation method can be repeatedly applied to multi-frame passive cavitation radio frequency signals generated under the same situation once constructed, and can also be applied to different situations (such as different pulse repetition frequencies and the like), so that great convenience is provided for data processing. In the invention, the full-aperture sampling signal is divided, the sub-aperture sampling signal is utilized to construct a sub-aperture sampling combined signal, and then the covariance matrix of the sub-aperture sampling combined signal is calculated, so that the covariance matrix is well estimated; and simultaneously, the covariance matrix is loaded diagonally, so that the robustness of the adaptive beam forming is enhanced. The feature space self-adaptive beam synthesis adopted in the invention integrates a self-adaptive beam synthesis method based on minimum variance undistorted response and a method for projecting self-adaptive weights into a signal subspace obtained by feature decomposition, and can effectively reduce the main lobe size and the side lobe level, thereby improving the resolution and the contrast of the passive cavitation imaging of the synchronous ultrasound in the transmitting time sequence. According to the invention, the dimension conversion matrix is constructed by carrying out main component analysis on the self-adaptive weights corresponding to the passive array simulation signals, and the dimension reduction processing is carried out on the covariance matrix corresponding to the passive cavitation radio frequency signals by utilizing the main component analysis, so that the dimension of the covariance matrix is reduced from the length of the sub-aperture to a smaller dimension, the huge calculation amount required by the inversion and the characteristic decomposition of the covariance matrix is reduced, the characteristic space self-adaptive beam forming can be carried out at a faster calculation speed, and the calculation speed of the passive cavitation imaging of the synchronous ultrasound in the transmission time sequence can be effectively improved.

Furthermore, the ultrasonic imaging transducer is operated in a non-transmitting and receiving-only mode to perform ultrasonic passive cavitation imaging, so that the problems that signals transmitted by the focused ultrasonic transducer interfere imaging and signals transmitted by the ultrasonic imaging transducer interfere cavitation activity when cavitation monitoring is performed by utilizing ultrasonic active imaging are avoided, and therefore the cavitation activity is monitored in real time and not interfered in the process of focusing ultrasonic action.

Further, according to the method, the optimal vertex coordinates in the traversing set of the vertex coordinates of the focused ultrasonic transducer are searched according to the number of the pixel points with the pixel values larger than the pixel value threshold in the delay superimposed beam forming image, and the minimum pixel points corresponding to the optimal vertex coordinates reflect the optimal imaging resolution, so that accurate position information of the focused ultrasonic transducer is obtained, and the quality of the passive cavitation imaging of the synchronous ultrasonic at the time of transmitting is improved.

Furthermore, the method averages the optimal vertex coordinates corresponding to the randomly selected multi-frame passive cavitation radio frequency signals, thereby being beneficial to reducing errors and improving the precision of the positioning coordinates of the focused ultrasonic transducer vertices.

Further, the invention constructs the passive array simulation signal according to the practical parameters of pulse length of the pulse signal transmitted by the focusing ultrasonic transducer, centroid frequency of frequency spectrum distribution of the passive cavitation radio frequency signal, signal sampling frequency, scale of the passive cavitation radio frequency signal and the space arrangement of the focusing ultrasonic transducer and the ultrasonic imaging transducer which are the same as the practical one, the passive array simulation signal has higher conformity with the practical passive cavitation radio frequency signal, and the adaptive weight sample obtained according to the passive array simulation signal has similar statistical characteristics with the practical adaptive weight, namely, the principal component in the sample can represent the practical adaptive weight, thereby leading the constructed dimension conversion matrix to be more reliable.

Furthermore, the invention takes the self-adaptive weight at each pixel point in the pixel grid calculated according to the passive array simulation signal as a sample to carry out principal component analysis on the self-adaptive weight, and the number of the samples (namely the number of the pixel points) is far greater than the variable number (namely the length of the sub-aperture), thereby meeting the statistical requirement.

Further, the invention replaces the last principal component vector with the direct current vector when constructing the dimension conversion matrix, so that the problem that the constraint condition of low-dimension domain self-adaptive beam forming cannot be met due to the mean value centralized pretreatment of principal component analysis can be avoided.

Furthermore, the invention provides two methods for calculating absolute transit time under the space setting of the focused ultrasonic transducer and the ultrasonic imaging transducer, and the absolute transit time under the space setting of the transducer which is most common in the current ultrasonic cavitation research can be calculated, so that the ultrasonic passive cavitation imaging method with synchronous transmission and time sequence has universal applicability.

Further, the dimension conversion matrix is utilized to carry out dimension reduction on the sub-aperture sampling combined signal corresponding to the passive cavitation radio frequency signal, and the low-dimension domain covariance matrix is obtained through the low-dimension domain sub-aperture sampling combined signal.

Furthermore, the invention adopts a cross spectrum measurement method to determine the dimension of the signal subspace of the covariance matrix of the low-dimensional domain, which is more beneficial to the improvement of imaging quality compared with the direct thresholding of the eigenvalue.

Drawings

FIG. 1 is a schematic diagram of an experimental system in an embodiment of the invention; wherein: 1-transparent water tank, 2-sound absorbing material, 3-focusing ultrasonic transducer, 4-pulse transmitting/receiving device, 5-ultrasonic imaging transducer, 6-clamping device, 7-high precision three-dimensional displacement table, 8-ultrasonic imaging data acquisition system, 9-main control computer, 10-multichannel waveform generator, 11-multichannel digital oscilloscope.

Fig. 2 is a result of 3-frame transmission time-series synchronous ultrasonic passive cavitation imaging obtained in the embodiment of the present invention, wherein: (a) a method based on delay-superimposed beam synthesis; (b) A method based on fast eigenspace adaptive beamforming.

Detailed Description

The invention is described in further detail below with reference to the drawings and examples. The examples are given solely for the purpose of illustration and are not intended to limit the scope of the invention.

Referring to fig. 1, the experimental system includes a transparent water tank 1, a sound absorbing material 2, a focused ultrasound transducer 3, a pulse transmitting/receiving device 4, an ultrasound imaging transducer 5, a clamping device 6, a high-precision three-dimensional displacement table 7, an ultrasound imaging data acquisition system 8, a main control computer 9, a multi-channel waveform generator 10, and a multi-channel digital oscilloscope 11. The bottom and the side wall of the transparent water tank 1 (for example, made of polycarbonate material, the length, the width and the height are respectively 50cm, 28cm and 28 cm) are provided with sound absorption materials 2, the upper surface of the transparent water tank 1 is open, one side wall of the transparent water tank 1 is provided with a circular hole capable of accommodating the focusing ultrasonic transducer 3, and the transparent water tank 1 is filled with deaerated water; a focused ultrasound transducer 3 (e.g., having a frequency of 1.6MHz, The aperture is 145 mm) is fixed on the side wall of the transparent water tank 1 through a circular hole, and the interface end of the focusing ultrasonic transducer 3 is connected with the output end of the pulse transmitting/receiving device 4; ultrasound imaging transducer 5 (e.g. number of array elements N _E The probe end of a linear array transducer with 128 array element intervals of 0.3mm is fixed on a clamping device 6 (for example, made of polycarbonate material), the clamping device 6 is fixed on a high-precision three-dimensional displacement table 7, and the interface end of an ultrasonic imaging transducer 5 is connected with the transducer interface of an ultrasonic imaging data acquisition system 8; the data interface of the ultrasonic imaging data acquisition system 8 is connected with the main control computer 9; the two channels of the multi-channel waveform generator 10 are connected to the external trigger port of the pulse transmitter/receiver 4 and the external trigger port of the ultrasound imaging data acquisition system 8, respectively, when the pulse transmitter/receiver 4 and the ultrasound imaging data acquisition system 8 are operating in the external trigger mode.

The pulse transmitter/receiver 4 activates the focused ultrasound transducer 3 to transmit a pulse signal into the deaerated water and generate cavitation activity in the deaerated water in an internal trigger mode or activates the focused ultrasound transducer 3 to transmit a pulse signal into a medium (e.g., deaerated water) and generate cavitation activity in the medium in an external trigger mode, depending on the set frequency, pulse length, pulse repetition frequency and intensity of the pulse signal.

The ultrasonic imaging data acquisition system 8 acquires a B-mode echo signal when the ultrasonic imaging transducer 5 is in a transmitting and receiving mode, so as to obtain a B-mode echo radio frequency signal; the ultrasonic imaging data acquisition system 8 acquires cavitation sound radiation signals when the ultrasonic imaging transducer 5 is in a non-transmitting and receiving only mode (namely a passive receiving mode) and the transmitting time sequence of the focusing ultrasonic transducer 3 is synchronous with the receiving time sequence of the ultrasonic imaging transducer 5, so as to obtain passive cavitation radio frequency signals, and the ultrasonic imaging data acquisition system 8 works in an external triggering mode at the moment; the working mode of the ultrasonic imaging transducer 5, the triggering mode of the ultrasonic imaging data acquisition system 8, the signal sampling frequency and the signal sampling point number are set in the main control computer 9, and the signals acquired by the ultrasonic imaging data acquisition system 8 are stored in the main control computer 9.

The main control computer 9 processes the B-mode echo radio frequency signals acquired by the ultrasonic imaging data acquisition system 8 and generates B-mode ultrasonic images, and the main control computer 9 processes the passive cavitation radio frequency signals acquired by the ultrasonic imaging data acquisition system 8 and generates a high-resolution and high-contrast transmission time sequence synchronous ultrasonic passive cavitation imaging result.

The multi-channel waveform generator 10 uses the trigger signals output by the two channels of the multi-channel waveform generator to synchronously trigger the pulse transmitter/receiver 4 and the ultrasonic imaging data acquisition system 8, so as to synchronize the transmission time sequence of the focusing ultrasonic transducer 3 and the receiving time sequence of the ultrasonic imaging transducer 5; the two channels of the multi-channel waveform generator 10 are connected to the two channels of the multi-channel digital oscilloscope 11, respectively, before triggering, so that the trigger signals output from the two channels of the multi-channel waveform generator 10 are checked by the multi-channel digital oscilloscope 11.

The invention utilizes the experimental system to develop the flow of the ultrasonic passive cavitation imaging with synchronous transmission and time sequence as follows:

(1) The triggering mode of the pulse transmitting/receiving device 4 is set as an internal triggering mode, the working mode of the ultrasonic imaging transducer 5 is set as a transmitting/receiving mode, and the position of the ultrasonic imaging transducer 5 is adjusted according to the B-mode ultrasonic image, and the specific flow is as follows in steps (1.1) - (1.4).

(1.1) setting the trigger mode of the pulse transmitter/receiver 4 to the internal trigger mode, and setting the frequency (e.g., 1.6 MHz), the pulse length (e.g., 5 to 10 cycles), the pulse repetition frequency (e.g., 100 to 1000 Hz), and the intensity (e.g., 50 to 90) of the pulse signal for exciting the focused ultrasound transducer 3 in the pulse transmitter/receiver 4;

(1.2) setting the operation mode of the ultrasonic imaging transducer 5 to a transmitting-receiving mode (e.g., a focus scanning B mode) in the main control computer 9;

(1.3) exciting the focused ultrasonic transducer 3 through the pulse transmitter/receiver 4 to generate cavitation activity in the deaerated water, and observing the cavitation activity generated in the deaerated water through the B-mode ultrasonic image;

(1.4) moving the clamping device 6 by means of the high precision three-dimensional displacement stage 7 according to the cavitation activity observed in the B-mode ultrasound image, the ultrasound imaging transducer 5 is adjusted to a suitable position (for example, the position where the signal of cavitation activity in the B-mode ultrasound image is strongest).

(2) Trigger signals are respectively arranged on two channels of the multi-channel waveform generator 10 and checked, parameters are respectively arranged in the pulse transmitter/receiver 4 and the main control computer 9, the pulse transmitter/receiver 4 and the ultrasonic imaging data acquisition system 8 are synchronously triggered by the trigger signals output by the two channels, and passive cavitation radio frequency signals are acquired and stored, and the specific flow is as follows in steps (2.1) - (2.6).

(2.1) setting trigger signals on two channels of the multi-channel waveform generator 10, respectively, wherein the trigger signal of the first channel (for example, the trigger frequency is 1000Hz, the trigger frequency is 100, and no delay) is used for triggering the pulse transmitter/receiver 4, and the trigger signal of the second channel (for example, the trigger frequency is 1000Hz, the trigger frequency is 100, and the trigger delay tau is equal to _Trig 0-50 mus) is used to trigger the ultrasound imaging data acquisition system 8;

(2.2) connecting two channels of the multi-channel waveform generator 10 with two channels of the multi-channel digital oscilloscope 11 respectively, checking whether the trigger signals output by the two channels of the multi-channel waveform generator 10 are correct or not through the multi-channel digital oscilloscope 11, and if not, checking and modifying parameter settings in the multi-channel waveform generator 10 until the trigger signals are correct and removing the multi-channel digital oscilloscope 11;

(2.3) connecting two channels of the multi-channel waveform generator 10 with external trigger ports of the pulse transmitter/receiver 4 and the ultrasonic imaging data acquisition system 8, respectively, and setting the trigger modes of the pulse transmitter/receiver 4 and the ultrasonic imaging data acquisition system 8 to the external trigger mode;

(2.4) setting the frequency (e.g., 1.6 MHz), pulse length (e.g., 1 cycle), pulse repetition frequency (e.g., 1000 Hz), and intensity (e.g., 90) of the pulse signal for exciting the focused ultrasound transducer 3 in the pulse transmitter/receiver 4; the operation mode of the ultrasonic imaging transducer 5 is set in the main control computer 9 to a passive reception mode, and the signal sampling frequency fs (e.g., fs=25 MHz ) Sum signal sample point number N _S (e.g. N _S ＝5000)；

(2.5) synchronously triggering the pulse transmitter/receiver 4 and the ultrasonic imaging data acquisition system 8 with the triggering signals output by the two channels of the multi-channel waveform generator 10 to synchronize the timing of the transmission by the focused ultrasonic transducer 3 and the reception by the ultrasonic imaging transducer 5; under the triggering of the triggering signal output by the first channel, the focusing ultrasonic transducer 3 emits pulse signals into a medium (such as deaerated water) and cavitation activity is generated in the medium, and under the triggering of the triggering signal output by the second channel, the ultrasonic imaging transducer 5 synchronously receives cavitation sound radiation signals;

(2.6) acquiring cavitation acoustic radiation signals passively received by the ultrasonic imaging transducer 5 with the ultrasonic imaging data acquisition system 8 to obtain N _F (e.g. N _F =100) frame passive cavitation radio frequency signal RF ^Expe,p (p＝1,2,...,N _F ) Wherein the p-th frame is passive cavitation RF signal ^Expe,p Comprises N _E The signal of each array element and the number of signal sampling points are N _S The method comprises the steps of carrying out a first treatment on the surface of the The obtained N _F The frame passive cavitation radio frequency signal is stored in the host computer 9.

(3) Establishing an equation of a tangent line or a tangent plane at the vertex of the focused ultrasonic transducer 3, establishing a calculation formula of a distance from a point in an imaging coordinate system to the tangent line or the tangent plane at the vertex of the focused ultrasonic transducer 3, establishing a calculation formula of a distance from the point in the imaging coordinate system to each array element of the ultrasonic imaging transducer 5, and establishing a calculation formula of absolute transit time, wherein the specific flow is as follows in steps (3.1) - (3.6).

(3.1) establishing a three-dimensional position coordinate system with the center of the ultrasonic imaging transducer 5 as an origin, with the transverse and axial directions of the ultrasonic imaging transducer 5 as an x-axis and a z-axis, respectively, and with the direction perpendicular to the imaging plane of the ultrasonic imaging transducer 5 as a y-axis;

(3.2) deleting the y-axis from the three-dimensional position coordinate system obtained in the step (3.1) to obtain an imaging coordinate system;

(3.3) establishing an equation of a tangent line or a tangent plane at the vertex of the focused ultrasonic transducer 3;

for the transducer space setting I, the equation for the tangent at the vertex of the focused ultrasound transducer 3 is:

sinα(x-x ^V )+cosα(z-z ^V )＝0

for the transducer space setting II, the equation for the tangent plane at the vertex of the focused ultrasound transducer 3 is:

sinα(y-y ^V )+cosα(z-z ^V )＝0

wherein x is ^V And z ^V The x-axis coordinate and the z-axis coordinate, y-axis coordinate of the three-dimensional position coordinate system of the vertex of the focused ultrasound transducer 3 in the step (3.1) or the imaging coordinate system in the step (3.2), respectively ^V Y-axis coordinates in the three-dimensional position coordinate system in step (3.1) for focusing the ultrasound transducer 3 vertex; in the space setting I of the transducer, the central axis of the focusing ultrasonic transducer 3 is in the imaging plane of the ultrasonic imaging transducer 5, and alpha is more than or equal to 0 and less than or equal to pi/2; in the space setting II of the transducer, the central axis of the focusing ultrasonic transducer 3 is intersected with the imaging plane of the ultrasonic imaging transducer 5 and is perpendicular to the transverse direction of the ultrasonic imaging transducer 5, and alpha is more than 0 and less than or equal to pi/2; alpha is an included angle between the central axis of the focusing ultrasonic transducer 3 and the central axis of the ultrasonic imaging transducer 5;

(3.4) establishing a calculation formula of a distance from a point in the imaging coordinate system to a tangent line or a tangent plane at the vertex of the focused ultrasonic transducer 3 in the step (3.2) according to the equation obtained in the step (3.3):

for the transducer space setting I, the calculation formula of the distance from the point with coordinates (x, z) to the tangent line at the vertex of the focused ultrasound transducer 3 is:

due to

The above formula can be simplified as d ¹ (x,z)＝|sinα(x-x ^V )+cosα(z-z ^V ) I, wherein i·irepresents taking absolute value;

for the transducer space setting II, the calculation formula of the distance from the point with coordinates (x, z) to the tangent plane at the vertex of the focused ultrasound transducer 3 is:

due to

And the y-axis coordinate of the point in the imaging coordinate system is 0, which can be simplified as d ¹ (x,z)＝|-sinα(y ^V )+cosα(z-z ^V )|；

(3.5) establishing a calculation formula of the distance from the point in the imaging coordinate system to each array element of the ultrasonic imaging transducer 5 in the step (3.2):

wherein i=1, 2,.. _E ，N _E For the number of array elements of the ultrasound imaging transducer 5,

coordinates of an ith array element of the ultrasonic imaging transducer 5;

(3.6) establishing a calculation formula of absolute transit time according to the calculation formulas obtained in the steps (3.4) and (3.5):

where c is the speed of sound propagation.

(4) And (3) carrying out delay superposition beam synthesis processing on the randomly selected passive cavitation radio frequency signals according to absolute transit time corresponding to the vertex coordinates in the traversal set of the vertex coordinates of the focused ultrasonic transducer 3, searching the optimal vertex coordinates from the traversal set according to a delay superposition beam synthesis diagram, and calculating the positioning coordinates of the vertex of the focused ultrasonic transducer 3, wherein the specific flow is as follows in steps (4.1) - (4.10).

(4.1) setting a grid of pixels under the imaging coordinate system in step (3.2)The coordinates of the pixel points in the pixel grid are recorded as

Where j=1, 2,.. _P ，N _P Is the number of pixels;

(4.2) setting a traversing set of vertex coordinates of the focused ultrasonic transducer 3, wherein the length of a traversing interval of x-axis coordinates, y-axis coordinates and z-axis coordinates is more than or equal to 10mm; the traversing step length of the x-axis coordinate and the y-axis coordinate is the pixel interval in the x-axis direction in the pixel grid in the step (4.1), and the traversing step length of the z-axis coordinate is the pixel interval in the z-axis direction in the pixel grid in the step (4.1);

(4.3) N from step (2.6) _F Randomly selecting N in frame passive cavitation radio frequency signal _CF (e.g. N _CF =10) frame passive cavitation radio frequency signal, denoted RF ^Expe,c (c＝1,2,...,N _CF )；

(4.4) calculating the absolute transit time at the jth pixel point in the pixel grid according to any vertex coordinate in the traversal set obtained in the step (4.2)

Wherein i=1, 2,.. _E The transducer space arrangement is shown in fig. 1; that is, (x, z) is made +.in the calculation formulas obtained in steps (3.4) and (3.5)>

Let->

Calculating the absolute transit time for any vertex coordinates in the traversal set by using the calculation formula obtained in the step (3.6)>

(4.5) absolute transit time +.A obtained according to step (4.4) >

Passive cavitation of randomly selected c-th frameFrequency signal RF ^Expe ^,c Performing delay superposition beam synthesis processing to obtain a delay superposition beam synthesis signal at the jth pixel point

/>

Wherein round {.cndot } represents rounding, RF _i ^Expe,c For RF ^Expe,c The signal of the i-th element (i=1, 2, N _E )，τ _Trig A trigger delay for the ultrasound imaging data acquisition system of step (2.1);

(4.6) repeating the step (4.5), and calculating to obtain a delayed superposition beam forming signal at each pixel point in the pixel grid in the step (4.1);

(4.7) performing Hilbert transform on the delay superimposed beam forming signals at each pixel point obtained in the step (4.6) to obtain a delay superimposed beam forming diagram;

(4.8) setting a pixel value threshold value and counting the number of pixel points with the pixel value larger than the pixel value threshold value in the delay superimposed beam forming image obtained in the step (4.7), wherein the pixel value threshold value is 0.1-0.5 times of the maximum pixel value in the delay superimposed beam forming image;

(4.9) repeating the steps (4.4) - (4.8) to obtain the number of pixel points with pixel values larger than a pixel value threshold in the time-delay superposition beam forming graph corresponding to all the vertex coordinates in the traversing set in the step (4.2), searching the minimum number of pixel points from the number of pixel points and recording the vertex coordinates corresponding to the minimum number of pixel points to obtain the optimal vertex coordinates corresponding to the randomly selected c-frame passive cavitation radio frequency signals;

(4.10) repeating the steps (4.4) to (4.9) to obtain randomly selected N _CF Optimal vertex coordinates corresponding to the frame passive cavitation radio frequency signals are carried out on the obtained N _CF The optimal vertex coordinates are respectively averaged in each direction (x-axis, y-axis and z-axis directions) to obtain the vertex positioning coordinates (x-axis) ^VL ,y ^VL ,z ^VL )。

(5) And calculating absolute transit time of each sound source in the simulated sound source group according to the vertex positioning coordinates of the focused ultrasonic transducer 3, constructing array simulation signals of each sound source according to the absolute transit time and the sound source radiation simulation signals, and superposing the array simulation signals of each sound source to obtain a passive array simulation signal, wherein the specific flow is shown in the following steps (5.1) - (5.7).

(5.1) setting coordinates of each sound source in the simulated sound source group under the imaging coordinate system in the step (3.2), wherein coordinates of the mth sound source are expressed as

m＝1,2,...,N _A ，N _A The number of sound sources (for example, 10-100), the distribution of the coordinates of each sound source is normal distribution (for example, the centers of the x-axis coordinate and the z-axis coordinate are respectively 0mm and 40mm, and the standard deviation of the x-axis coordinate and the z-axis coordinate is respectively 1mm and 1 mm);

(5.2) setting the simulation signal of the sound source radiation as a sine signal with a Hanning window, denoted as s _ae The sampling point number of the signal is

The time length of the signal is consistent with the pulse length of the pulse signal emitted by the focusing ultrasonic transducer 3 in the step (2.5) (for example, 1 period), the frequency of the signal is determined by the centroid frequency of the spectrum distribution of the passive cavitation radio frequency signal obtained in the step (2.6) (for example, the frequency is an integer MHz level frequency near the centroid frequency such as 5 MHz), and the signal sampling frequency of the signal is consistent with the signal sampling frequency fs set in the step (2.4) (for example, 25 MHz);

(5.3) setting the scale of the passive array simulation signal according to the scale of the passive cavitation radio frequency signal obtained in the step (2.6), namely, the passive array simulation signal contains N _E Simulation signals of each array element, and the sampling point number of the simulation signals of each array element is N _S ；

(5.4) the vertex positioning coordinates (x) of the focused ultrasound transducer 3 obtained according to step (4.10) ^VL ,y ^VL ,z ^VL ) Calculating the simulated sound in step (5.1)Absolute transit time at mth sound source in source group

Wherein i=1, 2,.. _E Transducer space arrangement referring to fig. 1; that is, let (x, z) be +.>

Ream (x) ^V ,y ^V ,z ^V ) Is (x) ^VL ,y ^VL ,z ^VL ) And calculating the absolute transit time +.A using the calculation formula obtained in step (3.6)>

(5.5) radiating a simulation signal s according to the sound source described in step (5.2) _ae And the absolute transit time obtained in step (5.4)

Constructing simulation signals of the ith array element of the ultrasonic imaging transducer 5 +.>

Wherein round {.cndot } represents rounding, τ _Trig For the trigger delay of the ultrasound imaging data acquisition system in step (2.1), k=1, 2,.. _S ；

(5.6) repeating the step (5.5) to obtain simulation signals of each array element of the ultrasonic imaging transducer 5, and constructing an array simulation signal RF of the mth sound source according to the simulation signals of each array element of the ultrasonic imaging transducer 5 ^Simu,m ；

(5.7) repeating the steps (5.4) - (5.6) to obtain array simulation signals of each sound source, and superposing the array simulation signals of each sound source to obtain a passive array simulationTrue signal RF ^Simu ：

(6) Calculating absolute transit time at each pixel point in a pixel grid according to vertex positioning coordinates of the focused ultrasonic transducer 3, extracting sampling points from the passive array simulation signals to obtain full-aperture sampling signals, calculating a covariance matrix by dividing the full-aperture sampling signals and diagonal loading, calculating self-adaptive weights, carrying out principal component analysis on the self-adaptive weights at each pixel point, and constructing a dimension conversion matrix according to principal component vectors, wherein the specific flow is as follows in steps (6.1) - (6.10).

(6.1) the vertex positioning coordinates (x) of the focused ultrasound transducer 3 obtained according to step (4.10) ^VL ,y ^VL ,z ^VL ) Calculating the absolute transit time at the j-th pixel point in the pixel grid in step (4.1)

Wherein i=1, 2,.. _E ，j＝1,2,...,N _P Transducer space arrangement referring to fig. 1; that is, let (x, z) be +.>

(6.2) the absolute time of flight obtained according to step (6.1)

The passive array simulation signal RF from step (5.7) ^Simu Extracting sampling points to obtain a full-aperture sampling signal +.>

Wherein the signal of the ith array element is

for RF ^Simu The signal of the i-th element (i=1, 2, N _E ) Round { _Trig The triggering delay of the ultrasonic imaging data acquisition system in the step (2.1) is that fs is the signal sampling frequency;

(6.3) sampling the full aperture sample signal obtained in the step (6.2)

Divided into N _E -l+1 overlapping sub-aperture sample signals +.>

/>

Wherein, l=1, 2,.. _E L+1, L is the length of the sub-aperture (e.g., N _E /2)，[·] ^T Representing a transpose;

(6.4) Using N obtained in step (6.3) _E -l+1 sub-aperture sampled signals

Construction of sub-aperture sampling combination signal>

(6.5) calculating the sub-aperture sample combination signal obtained in the step (6.4)

Covariance matrix of (2)

Wherein [ (S)] ^H Represents a conjugate transpose;

(6.6) the covariance matrix obtained in the step (6.5)

Diagonal loading is carried out to obtain covariance matrix after diagonal loading +.>

for a matrix of L rows and L columns, delta is a diagonal loading factor (e.g., 1/L), trace {.cndot } -represents a trace calculation, and I is a unitary matrix;

(6.7) the covariance matrix obtained in the step (6.6)

Calculating the adaptive weight +.>

Wherein inv [ · ] represents inversion operation, a is a direction vector, and elements in the vector are all 1;

(6.8) repeating the steps (6.1) - (6.7) to obtain the self-adaptive weight of each pixel point in the pixel grid;

and (6.9) taking the self-adaptive weights at each pixel point obtained in the step (6.8) as samples, and carrying out principal component analysis on the self-adaptive weights to obtain L principal component vectors:

(6.9.1) calculating covariance matrix of adaptive weights

Wherein mu ^Simu N is the average of the adaptive weights at each pixel point _P Is the number of pixels;

(6.9.2) for the covariance matrix obtained in step (6.9.1)

And (3) performing characteristic decomposition:

wherein, the diagonal line elements of Λ are eigenvalues (L) arranged in descending order, V= [ V ] ₁ ,v ₂ ,...,v _L ]V contains L eigenvectors corresponding to L eigenvalues arranged in descending order, namely L principal component vectors;

(6.10) selecting the first Q principal component vectors v corresponding to the maximum eigenvalue from the L principal component vectors obtained in the step (6.9) ₁ ,v ₂ ,...,v _Q-1 ,v _Q (Q.ltoreq.L, e.g. Q=8) and taking the last principal component vector v _Q The elements being replaced by elements

Then constructing a dimension conversion matrix C:

C＝[v ₁ ,v ₂ ,...,v _Q-1 ,dc]

the dimension conversion matrix C is a matrix of L rows and Q columns.

(7) And (3) performing dimension reduction processing on the covariance matrix after diagonal loading at each pixel point corresponding to any frame of passive cavitation radio frequency signals by utilizing a dimension conversion matrix, calculating low-dimensional domain self-adaptive weights, projecting the low-dimensional domain self-adaptive weights onto a signal subspace obtained by characteristic decomposition of the low-dimensional domain covariance matrix, calculating a rapid characteristic space self-adaptive beam forming signal at each pixel point according to the low-dimensional domain characteristic space self-adaptive weights and a low-dimensional domain sub-aperture sampling average signal, and performing Jing Xier Bert transformation, normalization and logarithmic processing to obtain a transmission time sequence synchronous ultrasonic passive cavitation imaging result, wherein the specific flow is as shown in the following steps (7.1) - (7.9).

(7.1) simulation of the signals RF by the passive arrays in step (6.2) ^Simu Replacing the signal with any frame of passive cavitation radio frequency signal obtained in the step (2.6), and sequentially calculating absolute transit time at the j-th pixel point in the pixel grid in the step (4.1) according to the steps (6.1) - (6.6)

And the full aperture sampling signal(s) at the j-th pixel point in the pixel grid in the step (4.1) corresponding to the passive cavitation radio frequency signal of the frame>

N _E -l+1 sub-aperture sample signals +.>

Sub-aperture sampling combined signal +.>

Covariance matrix of sub-aperture sampling combined signal +.>

Covariance matrix after diagonal loading ++>

Wherein p=1, 2,.. _F ，j＝1,2,...,N _P ：

(7.1.1) the vertex positioning coordinates (x) of the focused ultrasound transducer 3 obtained according to step (4.10) ^VL ,y ^VL ,z ^VL ) Calculating the absolute transit time at the j-th pixel point in the pixel grid in step (4.1)

Wherein i=1, 2,.. _E ，j＝1,2,...,N _P The transducer space arrangement is shown in fig. 1; namely, the calculation formulas obtained in the steps (3.4) and (3.5) are ordered

(7.1.2) the absolute time of flight obtained according to step (7.1.1)

Passive cavitation radio frequency signal RF of the p-th frame from step (2.6) ^Expe,p Extracting sampling points to obtain a full-aperture sampling signal +. >

Wherein the signal of the ith array element is +.>

for RF ^Expe,p The signal of the i-th element (i=1, 2, N _E ) Round { _Trig The triggering delay of the ultrasonic imaging data acquisition system in the step (2.1) is that fs is the signal sampling frequency;

(7.1.3) the full aperture sample signal obtained in the step (7.1.2)

Divided into N _E -l+1 overlapping sub-aperture sample signals +.>

(7.1.4) Using N obtained in step (7.1.3) _E -l+1 sub-aperture sampled signals

Construction of sub-aperture sampling combination signal>

(7.1.5 Calculating the sub-aperture sampling combined signal obtained in the step (7.1.4)

Covariance matrix>

Wherein [ (S)] ^H Represents a conjugate transpose;

(7.1.6) covariance matrix obtained in step (7.1.5)

(7.2) using the dimension conversion matrix C obtained in the step (6.10) to the covariance matrix obtained in the step (7.1) after diagonal loading

Performing dimension reduction to obtain a low-dimension domain covariance matrix +.>

Wherein [ (S)] ^H Represents the conjugate transpose of the object,

Is a matrix of L rows and L columns +.>

A matrix of Q rows and Q columns; reducing the dimension of the covariance matrix from L rows and L columns to Q rows and Q columns;

the above formula can be expressed as:

for the low-dimensional domain sub-aperture sampling combined signal, delta is the diagonal loading factor in the step (7.1), and zeta is the sub-aperture sampling combined signal +.>

Sum of squares of elements and number of sub-aperture sampling signals (N _E -ratio of l+1);

(7.3) the low-dimensional domain covariance matrix obtained according to step (7.2)

Calculating the adaptive weight of the low-dimensional domain +.>

/>

Wherein inv [. Cndot.]Represents inversion operation, b=c ^H a, C is the dimension conversion matrix obtained in the step (6.10), and a is the direction vector in the step (6.7);

(7.4) covariance matrix of the low-dimensional domain obtained in the step (7.2)

Performing characteristic decomposition to obtain signal subspace +.>

Self-adapting weight of low-dimensional domain obtained in step (7.3)>

Projecting the signal subspace to obtain the self-adaptive weight of the low-dimensional domain feature space>

Wherein the signal subspace

The dimension of (2) is determined according to a cross-spectrum measurement method (for example, the cross-spectrum measurement coefficient is 1% -5%);

(7.5) the dimension-conversion matrix C obtained in the step (6.10) and the N obtained in the step (7.1) _E -l+1 sub-aperture sampled signals

Calculating a low-dimensional domain sub-aperture sampling average signal +. >

(7.6) adaptive weighting of the low-dimensional domain feature space obtained according to step (7.4)

And (7.5) obtaining a low-dimensional domain sub-aperture sampling average signal +.>

Computing a fast eigenspace adaptive beamformed signal at the jth pixel point>

(7.7) repeating the steps (7.1) - (7.6), and calculating to obtain a rapid feature space self-adaptive beam synthesis signal at each pixel point in the pixel grid in the step (4.1);

(7.8) performing Hilbert transform on the rapid characteristic space self-adaptive beam synthesis signals at each pixel point obtained in the step (7.7) to obtain a rapid characteristic space self-adaptive beam synthesis image;

and (7.9) carrying out normalization and logarithmic processing on the rapid feature space self-adaptive beam forming diagram obtained in the step (7.8) to obtain a transmission time sequence synchronous ultrasonic passive cavitation imaging result corresponding to the passive cavitation radio frequency signal of any frame (namely, the p-th frame).

In the experimental system shown in fig. 1, the spatial arrangement of the focused ultrasound transducer 3 and the ultrasound imaging transducer 5 belongs to the above-mentioned transducer spatial arrangement I, where α=pi/2. And processing the 30 th frame, 60 th frame and 90 th frame passive cavitation radio frequency signals obtained by the experimental system to obtain 30 th frame, 60 th frame and 90 th frame transmission time sequence synchronous ultrasonic passive cavitation imaging results shown in figure 2, wherein figures 2 (a) and 2 (b) are imaging results obtained according to a traditional method based on time delay superposition beam synthesis and a method based on rapid characteristic space adaptive beam synthesis and used by the invention, and the imaging results are displayed in a dynamic range of 40 dB.

It can be seen that the main lobe in the imaging result of any frame shown in fig. 2 (a) has larger size and obvious side lobe interference, which indicates that the imaging resolution and the imaging contrast are lower (due to the non-self-adaptability of the delay superimposed beam synthesis, the traditional transmission time-sequence synchronous ultrasonic passive cavitation imaging method based on the delay superimposed beam synthesis has the defects of poor resolution and low contrast); and the main lobe size and the side lobe interference level in the corresponding frame imaging result shown in fig. 2 (b) are obviously reduced, which indicates that the imaging resolution and the imaging contrast are improved, and also indicates that the dimension conversion matrix constructed by the numerical simulation method has universal applicability to passive cavitation radio frequency signals of different frames.

Adopting the Area of the pixel point with the pixel value larger than-6 dB in the imaging result _-6dB Quantitative evaluation of imaging resolution, area _-6dB The smaller the imaging resolution is, the higher; CR (cr=20 lg (APV _inside /APV _outside ) Quantitatively evaluating imaging contrast, the greater the CR, the higher the imaging contrast, wherein APV _inside And APV _outside The average value of the pixel values corresponding to the pixel points with the pixel value larger than-6 dB and the pixel points with the pixel value smaller than-6 dB in the imaging result without logarithmic processing is respectively obtained. Calculated, the Area corresponding to the 3-frame imaging result in FIG. 2 (a) _-6dB Respectively 0.75mm ² 、1.51mm ² And 1.24mm ² The corresponding CR is 39.81dB, 38.11dB and 41.48dB, respectively; area corresponding to 3 frame imaging results in FIG. 2 (b) _-6dB Respectively 0.41mm ² 、0.80mm ² And 0.59mm ² The corresponding CR is 47.69dB, 44.37dB and 49.20dB, respectively. The analysis shows that the invention can effectively and simultaneously improve the resolution and the contrast of the passive cavitation imaging of the synchronous ultrasonic of the time sequence of the transmission.

The computational burden of eigenspace adaptive beamforming is mainly caused by the inversion and eigen decomposition of the covariance matrix, and the floating point operands required for the inversion and eigen decomposition of the covariance matrix are

Wherein (1)>

Is the number of rows or columns of the covariance matrix. The invention reduces the dimension of the covariance matrix from L rows and L columns (such as L=64) to Q rows and Q columns (such as Q=8) by using the dimension conversion matrix constructed by a numerical simulation method, so that the floating point operand is from 2L ³ /3+21L ³ = 5679787 decrease to 2Q ³ /3+21Q ³ = 11094, enabling feature space adaptive beamforming at faster computational speeds and thus increasing the computational speed of transmit time-synchronized ultrasound passive cavitation imaging.

The invention has the following advantages:

(1) The invention allows the passive cavitation radio frequency signal to be processed by utilizing absolute transit time information by synchronizing the time sequence of the transmission of the focused ultrasonic transducer and the receiving of the ultrasonic imaging transducer, thereby improving the axial resolution of the ultrasonic passive cavitation imaging under the condition of short pulse transmission. Meanwhile, the invention searches the optimal vertex coordinates and calculates the positioning coordinates of the focused ultrasonic transducer vertices according to the time-delay superposition beam forming graph, and can provide accurate position information of the focused ultrasonic transducer for calculating absolute transit time, thereby obtaining better imaging quality.

(2) According to the invention, the dimension conversion matrix is constructed by a numerical simulation method, so that the problem of constructing a corresponding dimension conversion matrix each time when each frame of passive cavitation radio frequency signal is processed can be avoided, and meanwhile, the dimension conversion matrix is not required to be constructed by a pre-experiment; the dimensional transformation matrix constructed by the invention can be recycled by constructing only once, thereby providing great convenience for data processing. And the invention constructs the passive array simulation signal according to the actual parameters (the focused ultrasonic transducer emission parameters, the passive cavitation radio frequency signal acquisition parameters and the centroid frequency of the spectrum distribution of the passive cavitation radio frequency signal) and the transducer space arrangement which is the same as the actual, and the self-adaptive weight sample obtained according to the signal has similar statistical characteristics with the self-adaptive weight in the actual, thereby enhancing the reliability of the constructed dimension conversion matrix. In the process of constructing the dimension conversion matrix, the self-adaptive weight at each pixel point in the pixel grid is used as a sample for principal component analysis, and the last principal component vector is replaced by the direct current vector, so that the statistical requirement of principal component analysis is met, and the problem that the constraint condition of low-dimension domain self-adaptive beam synthesis cannot be met is avoided.

(3) The invention adopts the characteristic space self-adaptive beam synthesis, and can effectively reduce the main lobe size and the side lobe level by self-adaptive beam synthesis based on the minimum variance undistorted response and projecting the self-adaptive weight to the signal subspace obtained by characteristic decomposition, thereby synchronously improving the resolution and the contrast of the synchronous ultrasonic passive cavitation imaging in the transmitting time sequence. And the covariance matrix is calculated through sub-aperture average and diagonal loading, so that the covariance matrix can be well estimated, and the robustness of self-adaptive beam forming is enhanced. The invention adopts a cross spectrum measurement method to determine the dimension of the signal subspace, which is also beneficial to the improvement of imaging quality.

(4) According to the invention, the dimension conversion matrix constructed by carrying out principal component analysis on the self-adaptive weights corresponding to the passive array simulation signals is utilized, so that the dimension of the covariance matrix is reduced, and the huge calculation amount required by inversion and feature decomposition of the covariance matrix is reduced, thereby improving the calculation speed of feature space self-adaptive beam synthesis and accordingly improving the calculation speed of time-sequence synchronous ultrasonic passive cavitation imaging during transmission. The method for reducing the dimension of the sub-aperture sampling combined signal corresponding to the passive cavitation radio frequency signal and obtaining the low-dimension domain covariance matrix through the signal obtained by reducing the dimension can effectively reduce the calculated amount of calculating the low-dimension domain covariance matrix when the length of the sub-aperture is large, and is also beneficial to improving the calculation speed of the synchronous ultrasonic passive cavitation imaging during the transmission.

(5) The invention provides two methods for calculating absolute transit time under the spatial arrangement of a focused ultrasonic transducer and an ultrasonic imaging transducer, so that the method for transmitting time-sequence synchronous ultrasonic passive cavitation imaging by high-resolution high-contrast rapid calculation is suitable for the spatial arrangement of the transducers which are most common in the current ultrasonic cavitation research. The invention can reconstruct the distribution of cavitation activity in the ultrasonic field with high resolution, high contrast and high speed, provides a powerful imaging means for monitoring the cavitation space-time dynamics evolution process of various ultrasonic cavitation applications such as high-intensity tissue damage, low-intensity blood brain barrier opening and the like, and lays a solid foundation for clarification of relevant biophysical mechanisms and regulation and optimization of ultrasonic emission parameters.

Claims

1. A high-resolution high-contrast rapid-calculation transmission time-sequence synchronous ultrasonic passive cavitation imaging method is characterized in that: the method comprises the following steps:

1) Synchronizing the time sequence of the emission of the focusing ultrasonic transducer (3) and the receiving of the ultrasonic imaging transducer (5) through synchronous triggering, and collecting cavitation sound radiation signals passively received by the ultrasonic imaging transducer to obtain passive cavitation radio frequency signals;

2) Setting pixel grids under an imaging coordinate system, calculating absolute transit time of each pixel point in the pixel grid corresponding to each vertex coordinate in a traversing set of vertex coordinates of a focused ultrasonic transducer (3), respectively carrying out delay superposition beam synthesis processing on a plurality of frames of passive cavitation radio frequency signals selected from the passive cavitation radio frequency signals acquired in the step 1 according to the absolute transit time to obtain delay superposition beam synthesis signals of each pixel point corresponding to each vertex coordinate in the traversing set, carrying out Hilbert transform on the delay superposition beam synthesis signals of each pixel point corresponding to each vertex coordinate in the traversing set to obtain delay superposition beam synthesis images corresponding to each vertex coordinate in the traversing set, searching for optimal vertex coordinates in the traversing set according to the delay superposition beam synthesis images corresponding to each vertex coordinate in the traversing set, and calculating positioning coordinates of the focused ultrasonic transducer (3) according to the optimal vertex coordinates respectively searched under the passive cavitation radio frequency signals of different frames;

3) Setting the scale of sound source radiation simulation signals and passive array simulation signals, setting the coordinates of each sound source in a simulation sound source group under an imaging coordinate system, calculating absolute transit time at each sound source in the simulation sound source group according to the vertex positioning coordinates of a focused ultrasonic transducer (3), constructing simulation signals of each array element of the ultrasonic imaging transducer (5) according to the absolute transit time and the sound source radiation simulation signals, constructing array simulation signals of corresponding sound sources according to the simulation signals of each array element of the ultrasonic imaging transducer (5), and superposing the array simulation signals of each sound source to obtain the passive array simulation signals;

4) Calculating absolute transit time of each pixel point in the pixel grid according to vertex positioning coordinates of a focused ultrasonic transducer (3), respectively extracting sampling points from passive array simulation signals according to the absolute transit time to obtain full-aperture sampling signals of the corresponding pixel points, dividing the full-aperture sampling signals of the corresponding pixel points into a plurality of overlapped sub-aperture sampling signals, constructing sub-aperture sampling combined signals by utilizing the sub-aperture sampling signals, calculating covariance matrixes of the sub-aperture sampling combined signals, carrying out diagonal loading on the covariance matrixes, calculating self-adaptive weights of the corresponding pixel points according to the covariance matrixes after diagonal loading, carrying out principal component analysis on the self-adaptive weights of the pixel points to obtain principal component vectors, and constructing a dimension conversion matrix according to the principal component vectors;

2. The high resolution high contrast fast computing transmit time synchronized ultrasound passive cavitation imaging method of claim 1, wherein: in the step 2, searching the optimal vertex coordinates in the traversal set specifically includes the following steps:

3. The high resolution high contrast fast computing transmit time synchronized ultrasound passive cavitation imaging method of claim 1, wherein: in the step 3, the sound source radiation simulation signal is a sine signal with a Hanning window, the time length of the sound source radiation simulation signal is consistent with the pulse length of a pulse signal emitted by the focusing ultrasonic transducer (3), the frequency of the sound source radiation simulation signal is determined by the centroid frequency of the spectrum distribution of the passive cavitation radio frequency signal, the sampling frequency of the sound source radiation simulation signal is consistent with the sampling frequency of the passive cavitation radio frequency signal, and the scale of the passive array simulation signal is consistent with the scale of the passive cavitation radio frequency signal; in the step 3, the space setting of the transducer used for calculating the absolute transit time of each sound source in the simulated sound source group is the same as the space setting of the focusing ultrasonic transducer (3) and the ultrasonic imaging transducer (5) in the step 1; in the step 4, the space setting of the transducer used for calculating the absolute transit time at each pixel point in the pixel grid is the same as the space setting of the focusing ultrasonic transducer (3) and the ultrasonic imaging transducer (5) in the step 1.

4. The high resolution high contrast fast computing transmit time synchronized ultrasound passive cavitation imaging method of claim 1, wherein: in the step 3, the simulation signal of any array element of the ultrasonic imaging transducer in the constructed array simulation signal of any sound source is expressed as:

wherein RF _i ^Simu,m (k) I=1, 2, N for simulation signals of the i-th array element in the array simulation signals of the m-th sound source in the simulated sound source group _E ，N _E For the number of array elements of the ultrasound imaging transducer (5), k=1, 2,.. _S ，N _S For the number of samples of the passive cavitation radio frequency signal, m=1, 2,.. _A ，N _A To simulate the number of sound sources in a sound source group, round {.

For absolute transit time at mth sound source calculated from focused ultrasound transducer (3) vertex positioning coordinates, τ _Trig For acquiring the triggering delay of cavitation acoustic radiation signals, fs is the sampling frequency of passive cavitation radio frequency signals, s _ae For sound source radiation simulation signal->

5. The high resolution high contrast fast computing transmit time synchronized ultrasound passive cavitation imaging method of claim 1, wherein: in the step 4, the main component analysis of the adaptive weights at each pixel point specifically includes the following steps:

Taking the self-adaptive weight at each pixel point in the pixel grid calculated according to the passive array simulation signal as a sample, calculating a covariance matrix of the self-adaptive weight, and then carrying out feature decomposition on the covariance matrix to obtain L feature vectors corresponding to L feature values arranged in a descending order, namely obtaining L principal component vectors;

in the step 4, the construction of the dimension conversion matrix specifically includes the following steps:

The resulting dimensional transformation matrix is expressed as: />

C＝[v ₁ ,v ₂ ,...,v _Q-1 ,dc]。

6. The high resolution high contrast fast computing transmit time synchronized ultrasound passive cavitation imaging method of claim 1, wherein: in the step 2, the step 3 and the step 4, the calculation of the absolute transit time specifically includes the following steps:

s1, taking the center of an ultrasonic imaging transducer (5) as an origin, taking the transverse direction and the axial direction of the ultrasonic imaging transducer (5) as an x-axis and a z-axis respectively, and taking the direction perpendicular to an imaging plane of the ultrasonic imaging transducer (5) as a y-axis, and establishing a three-dimensional position coordinate system;

S3, establishing an equation of a tangent line or a tangent plane at the vertex of the focused ultrasonic transducer (3):

for the transducer space setting I, the equation of the tangent line at the vertex of the focused ultrasonic transducer (3) is:

sinα(x-x ^V )+cosα(z-z ^V )＝0

for the transducer space setting II, the equation of the tangential plane at the vertex of the focused ultrasound transducer (3) is:

sinα(y-y ^V )+cosα(z-z ^V )＝0

wherein x is ^V And z ^V Respectively an x-axis coordinate and a z-axis coordinate of the vertex of the focusing ultrasonic transducer (3) in the three-dimensional position coordinate system, y ^V -a y-axis coordinate in the three-dimensional position coordinate system for the vertex of the focused ultrasound transducer (3); in the space setting I of the transducer, the central axis of the focusing ultrasonic transducer (3) is in the imaging plane of the ultrasonic imaging transducer (5), and alpha is more than or equal to 0 and less than or equal to pi/2; in the space setting II of the transducer, the central axis of the focusing ultrasonic transducer (3) is intersected with the imaging plane of the ultrasonic imaging transducer (5) and is perpendicular to the transverse direction of the ultrasonic imaging transducer (5), and alpha is more than 0 and less than or equal to pi/2; alpha is an included angle between the central axis of the focusing ultrasonic transducer (3) and the central axis of the ultrasonic imaging transducer (5);

for the transducer space setting I, the calculation formula of the distance from the point with the coordinates of (x, z) to the tangent line at the vertex of the focusing ultrasonic transducer (3) is as follows:

d ¹ (x,z)＝|sinα(x-x ^V )+cosα(z-z ^V )|

Wherein, |·| represents taking absolute values;

for the transducer space setting II, the calculation formula of the distance from the point with the coordinates of (x, z) to the tangent plane at the vertex of the focusing ultrasonic transducer (3) is as follows:

d ¹ (x,z)＝|-sinα(y ^V )+cosα(z-z ^V )|

s5, establishing a calculation formula of the distance from a point with coordinates (x, z) in an imaging coordinate system to each array element of the ultrasonic imaging transducer (5):

wherein i=1, 2,.. _E ，

Coordinates of an ith array element of the ultrasonic imaging transducer (5);

where c is the speed of sound propagation.

7. The high resolution high contrast fast computing transmit time synchronized ultrasound passive cavitation imaging method of claim 1, wherein: in the step 5, the calculation formula of the low-dimensional domain covariance matrix is as follows:

where j=1, 2,.. _P ，N _P N is the number of pixel points _E For the number of array elements of the ultrasonic imaging transducer (5), L is the length of the sub-aperture,

and

respectively a low-dimensional domain sub-aperture sampling combined signal and a sub-aperture sampling combined signal at a j pixel point corresponding to a p-th frame passive cavitation radio frequency signal, wherein delta is a diagonal loading factor, and zeta is +.>

The ratio of the sum of squares of the elements of (a) to the number of sub-aperture sample signals, C is the dimension conversion matrix.

8. The high resolution high contrast fast computing transmit time synchronized ultrasound passive cavitation imaging method of claim 1, wherein: in the step 5, the dimensionality of the signal subspace obtained by the low-dimensional domain covariance matrix through characteristic decomposition is determined according to a cross spectrum measurement method, wherein the cross spectrum measurement coefficient is 1% -5%.

9. The high resolution high contrast fast computing transmit time synchronized ultrasound passive cavitation imaging method of claim 1, wherein: in the step 5, the calculation formula of the low-dimensional domain sub-aperture sampling average signal is as follows:

where j=1, 2,.. _P ，N _P N is the number of pixel points _E Is the number of array elements of the ultrasonic imaging transducer (5), L is the length of the sub-aperture, C is the dimension conversion matrix,

10. The system comprises a focused ultrasound transducer vertex positioning coordinate calculation module, a passive array simulation signal construction module, a dimension conversion matrix construction module, a rapid feature space self-adaptive beam synthesis module and an image display module;

The focused ultrasonic transducer vertex positioning coordinate calculation module is used for setting pixel grids under an imaging coordinate system, calculating absolute transit time of each pixel point in a pixel grid corresponding to each vertex coordinate in a traversing set of vertex coordinates of a focused ultrasonic transducer (3), respectively carrying out delay superposition beam synthesis processing on a plurality of frames of passive cavitation radio frequency signals selected from the acquired passive cavitation radio frequency signals according to the absolute transit time, carrying out Hilbert transformation on the delay superposition beam synthesis signals at each pixel point corresponding to each vertex coordinate in the traversing set obtained by processing, searching for an optimal vertex coordinate in the traversing set according to a delay superposition beam synthesis diagram corresponding to each vertex coordinate in the traversing set obtained by transformation, and calculating the vertex positioning coordinate of the focused ultrasonic transducer (3) according to the optimal vertex coordinate respectively found under the selected passive cavitation radio frequency signals of different frames;

the passive array simulation signal construction module is used for setting the scale of sound source radiation simulation signals and passive array simulation signals, setting the coordinates of each sound source in a simulation sound source group under an imaging coordinate system, calculating absolute transit time at each sound source in the simulation sound source group according to the vertex positioning coordinates of the focused ultrasonic transducer (3) obtained by the focused ultrasonic transducer vertex positioning coordinate calculation module, constructing simulation signals of each array element of the ultrasonic imaging transducer (5) according to the absolute transit time and the sound source radiation simulation signals, constructing array simulation signals of corresponding sound sources according to the simulation signals of each array element of the ultrasonic imaging transducer (5), and obtaining the passive array simulation signals by superposing the array simulation signals of each sound source;

The dimension conversion matrix construction module is used for calculating absolute transit time at each pixel point in the pixel grid according to the vertex positioning coordinates of the focused ultrasonic transducer (3) obtained by the vertex positioning coordinates calculation module of the focused ultrasonic transducer, respectively extracting sampling points from the passive array simulation signals obtained by the passive array simulation signal construction module according to the absolute transit time, dividing the full-aperture sampling signals at the corresponding pixel points obtained by extraction into a plurality of overlapped sub-aperture sampling signals and utilizing the sub-aperture sampling signals to construct a sub-aperture sampling combined signal, calculating a covariance matrix of the sub-aperture sampling combined signal and carrying out diagonal loading on the covariance matrix, calculating self-adaptive weights at the corresponding pixel points according to the covariance matrix after diagonal loading, carrying out principal component analysis on the self-adaptive weights at each pixel point, and constructing a dimension conversion matrix according to principal component vectors obtained by analysis;

the fast feature space adaptive beam synthesis module is used for extracting and dividing a plurality of overlapped sub-aperture sampling signals at corresponding pixel points from any frame of acquired passive cavitation radio frequency signals according to the absolute transit time calculated in the dimension conversion matrix construction module, calculating a corresponding covariance matrix by using sub-aperture sampling combined signals constructed by the sub-aperture sampling signals, carrying out diagonal loading on the covariance matrix, carrying out dimension reduction processing on the covariance matrix after diagonal loading by using the dimension conversion matrix obtained by the dimension conversion matrix construction module, calculating low dimension domain adaptive weights at the corresponding pixel points according to the low dimension domain covariance matrix at the corresponding pixel points obtained by the dimension reduction processing, projecting the low dimension domain adaptive weights onto the signal subspace obtained by the feature decomposition of the low dimension domain covariance matrix, calculating low dimension domain sub-aperture sampling average signals at the corresponding pixel points according to the dimension conversion matrix and the sub-aperture sampling signals, and carrying out fast synthesis on the fast feature space adaptive beam synthesis signals at the corresponding pixel points by using the low dimension domain adaptive weights at the corresponding pixel points and the low dimension domain sub-aperture sampling average signal;